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The Risk Factors of Readmission in Postoperative Gynecologic Oncology Patients at a Single Institution
John M Nakayama1, Jennie P Ou, Caroline Friedman
1*Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, University of Virginia Medical Center; †University of Virginia Medical School; and ‡Translational Research and Applied Statistics, University of Virginia, Charlottesville, VA.
Introduction:
Hospital readmission rates are an important measure of quality care and have recently been tied to reimbursement. This study seeks to identify the risk factors for postoperative readmission in patients treated by a gynecologic oncology service.
Methods:
A 7-year retrospective review (2007-2013) of all patients operated on by the University of Virginia gynecologic oncology service who were readmitted within 30 days of discharge was performed. Abstracted data included demographics, dates of surgery, operative details, cancer history, and relevant medical history. The readmitted patients (n = 166) were compared with randomly selected controls (n = 168) from the same service in a matching time frame and analyzed using univariate and multivariate models.
Results:
In the study period, 2993 operations were performed. One hundred sixty-six unique patients (5.5%) were readmitted within 30 days of discharge from their operative procedure. On multivariate analysis, the factors that were associated with a higher risk of readmission were a history of psychiatric disease, postoperative complication, type of insurance, surgical modality, and lysis of adhesions at the time of surgery. The most common readmission diagnoses were infection (44%), nausea/vomiting (28%), thrombosis (6%), bowel leak (4%), and bleeding (4%).
Conclusions:
Postoperative readmissions are a common problem and are increasingly important as a measure of quality. Although patients were generally admitted for infections or gastrointestinal complaints, we also found that individual factors such as mental health and socioeconomic status also contributed. Our data suggest that we can preoperatively identify high-risk individuals for whom extra resources can be directed postoperatively to avoid unnecessary readmissions.
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